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Brake judder is a brake induced vibration that a vehicle driver experiences in the steering wheel or floor panel at highway speeds during vehicle deceleration. The primary cause of this disturbance phenomenon is the brake torque variation (BTV). Virtual CAE tools from both kinematics and compliance standpoints have been applied in analyzing sensitivities of the vehicle systems to BTV. This paper presents a recently developed analytical approach that identifies parameters of steering and suspension systems for achieving optimal settings that desensitize the vehicle response to BTV. The analytical steps of this integrated approach started with creating a lumped mass noise-vibration-harshness (NVH) control model and a separate multi-body dynamics (MBD) suspension model. Then, both models were linked to run in a sequence through optimization software so the results from the MBD model were used as quasi-static inputs to the lumped mass NVH model.

Dimensional variation analysis is a critical step of the dimensional management process for understanding the predicted dimensional variation from manufacturing process. Through analysis, product and process capabilities were evaluated, and the variation can be predicted and documented at each step of the build. The objective to develop the concurrent virtual dimensional analytical (CVDA) methods was to concurrently design a product and manufacturing process insensitive to part and process variations by integrating various analytical tools in literatures and in industry practice. The allowable variation targets of the product that meet the functional requirements are defined with the geometric dimensioning and tolerancing (GD&T) drawings. If at all possible, each part’s datum features defined on the drawing are required to be coordinated with the locating features of production tools.

Design for Six Sigma (DFSS) is a product improvement process based on statistical problem solving capabilities which is typically followed IDDOV approach - Identify, Define, Develop, Optimize, and Verify the design. Flexible inspection system (FIS) is defined as one where the inspection routines are not fixed but are determined just prior to performing the inspection [1]. In FIS the inspection stations have the capacity of performing different inspection routines according to a global inspection strategy. In this paper, the IDDOV steps, as well as some DFSS variation analysis techniques, are applied with the FIS to provide an analytical framework for an optimized strategy of real time inspection allocations.

The concept of design for six sigma (DFSS) offers a framework to design a product and process right the first time. In general, Taguchi's robust design method has been widely adapted in design optimization, which is a critical phase in any DFSS projects. The objective of the paper is to develop an advanced strategy in selecting an optimized product design and manufacturing process that should be insensitive to various multivariate variation patterns of the multi-stage manufacturing system. A Monte Carlo variation simulation based method is presented that integrates Mohalanobis Distance (MD) method, a discriminant analysis technique, to analyze the manufacturing variation patterns detected by using the multivariate statistical tool, such as principal component analysis (PCA). The proposed method will be explained with an example of an automotive assembly.